| Autor: |
Zhuo Gong, Daisuke Saito, Nobuaki Minematsu |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Applied Sciences, Vol 12, Iss 19, p 9690 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2076-3417 |
| DOI: |
10.3390/app12199690 |
| Popis: |
Language models (LM) have played crucial roles in automatic speech recognition (ASR), whether as an essential part of a conventional ASR system composed of an acoustic model and LM, or as an integrated model to enhance the performance of novel end-to-end ASR systems. With the development of machine learning and deep learning, language modeling has made great progress in natural language processing applications. In recent years, efforts have been made to leverage the advantages of novel LM to ASR. The most common way to apply an integration is still shallow fusion because it can be easily implemented by zero-overhead while obtaining significant improvement. Our method can further enhance the applicability of shallow fusion without hyperparameter tuning while maintaining similar performance. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
